Personal Reading List: 3Q2022
My personal reading list for July, August, and September 2022.
Color Key: Special Notes, Completed Reading. Updated throughout the Quarter.
At Bat (Schnell)
AWS Certified Database – Specialty (DBS-C01) Certification, by Kate Gawron, Packt Publishing, 2022. Copy provided by Packt publicist Nivedita Singh.
Machine Learning Engineering in Action, by Ben Wilson, Manning, 2022. Copy provided by author Ben Wilson.
At Bat (Langsam)
The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page, Basic Books, 2018.
Practical Statistics for Data Scientists: 50 Essential Concepts, by Peter Bruce and Andrew Bruce, O'Reilly, 2017. Copy provided by MarkLogic.
On Deck
Fluent Python: Clear, Concise, and Effective Programming, by Luciano Ramalho, O'Reilly, 2015.
Interpretable Machine Learning: A Guide for Making Black Box Models Explainable (Second Edition), by Christoph Molnar, Independently Published, 2022.
In the Hole
97 Things Every Data Engineer Should Know, edited by Tobias Macey, O'Reilly, 2021. Copy provided by Promethium.
Presto: The Definitive Guide, by Matt Fuller, Manfred Moser, and Martin Traverso, O'Reilly, 2020. Copy provided by Starburst.